Due to the increased amounts of data being generated, stored, and processed today, operational databases are constructed, categorized, and formatted for operational efficiency (e.g., throughput, processing speed, and storage capacity). The raw data found in these operational databases often exist as rows and columns of numbers and code that appear bewildering and incomprehensible to business analysts and decision makers. Furthermore, the scope and vastness of the raw data stored in modern databases render it harder locate usable information. Hence, “analytic applications” have been developed in an effort to help interpret, analyze, and compile the data so that it may be more readily understood by a business analyst. These applications map, sort, categorize, and summarize the raw data before it is presented for display, so that individuals can interpret data and use it as the basis for making decisions. However, for users not experienced in the nuances of constructing a query, the amount of effort required to get specific data may be burdensome to many users.
Given the many different types of source data available, and the many ways that the source data can be transformed and combined, large amounts of data are available that can be difficult for a user to navigate. An example is a user who has identified a problem area in business performance which requires further investigation. This user may need to go through a number of fields of data in order to identify exactly what has caused the problem. For a user who is skilled in constructing a query, this may be an easy task, but less skilled users may find it difficult to navigate the database and find the root cause of the problem.
Another user may spend a great deal of time searching through databases seeking particular items of information such as the business metrics that provide a concise measure of the performance or efficiency of a business (e.g., total sales revenue, margin, etc.). Because the information may change dramatically and/or frequently, a user may need to make such time-consuming searches on a regular basis. For a user who must access data regularly, these searches can take an inordinate amount of time.
Hence, it is desirable to facilitate access to pertinent information in the large databases defined by analytic applications, especially items of information of particular interest to a user. It is also desirable for the user to be able to reach a particular data field, or conduct multiple searches of related data fields, without having to recreate the entire search each time. The present invention provides a method and system that meet the above needs.